Alkalmazott Matematikai és Valószínűségszámítási Tanszék

1.

Martos, R., Szokol, Á., Veres, M., Gáll, J., Csik, A., Hegedűs, C., Keczánné Üveges, A., Tóth, E. R., Szalóki, M.: Evaluation of Two-Body Wear of Nanocomposites With Different Filler Morphology and Composition Using White-Light Interferometry.
Int J Dent. 2026, 1-14, (cikkazonosító: 8929009), 2026.

doi DEA

Folyóirat-mutatók:

Q1 Dentistry (miscellaneous) (2025)

2.

Mayer, M. J., Baran, Á., Lerch, S., Horat, N., Yang, D., Baran, S.: Post-processing of ensemble photovoltaic power forecasts with distributional and quantile regression methods.
Sol. Energy. 307, 1-36, (cikkazonosító: 114361), 2026.

doi DEA

Folyóirat-mutatók:

Q1 Materials Science (miscellaneous) (2025)

Q1 Renewable Energy, Sustainability and the Environment (2025)

3.

Mayer, M. J., Baran, S.: Probabilistic PV forecasting.
In: AI-Based Forecasting of Solar Photovoltaics Power Generation / Elham Shirazi; Wilfried van Sark (eds), The Institution of Engineering and Technology (The IET), London, 149-176, 2026. ISBN: 9781837240197

doi DEA

4.

Baran, S., Nagy-Lakatos, M.: Statistical post-processing of operational dual-resolution wind-speed ensemble forecasts.
Q. J. R. Meteorol. Soc. [Epub ahead of print], 2026.

doi DEA

Folyóirat-mutatók:

Q1 Atmospheric Science (2025)

5.

Masasila, N. H., Fazekas, I.: Strong law of large numbers for [phi]-sub-Gaussian random variables under sub-linear expectation spaces.
Probab. Uncertain. Quant. Risk. [Submitted], 1-10, 2026.

DEA

6.

Nádasi, L., Kovács, S., Petneházi, G., Trón, Z.: The analysis of stability in the EU convergence clubs by using Poincaré plot features.
Reg. Stat. 16 (2), 318-342, 2026.

doi DEA WoS Scopus

Folyóirat-mutatók:

Q1 Cultural Studies (2025)

Q3 Economics and Econometrics (2025)

Q3 Geography, Planning and Development (2025)

Q3 Public Administration (2025)

Q3 Statistics and Probability (2025)

7.

Fazekas, I., Fórián, L.: A family of network evolution models with moderate density.
Stat. Pap. 66 (5), 1-18, (cikkazonosító: 105), 2025.

doi DEA WoS

Folyóirat-mutatók:

Q2 Statistics and Probability

Q2 Statistics, Probability and Uncertainty

8.

Rácz, A.: A MILP model for one dimensional cutting stock problem with adjustable leftover threshold and cutting cost.
IJOCTA. 15 (2), 215-224, 2025.

doi DEA

Folyóirat-mutatók:

Q2 Applied Mathematics

Q2 Control and Optimization

9.

Ali, A. A. A., Kovásznai, G., Khalid, M.: Automated fair team formation in STEAM activities using Satisfiability Modulo Theories (SMT).
Ann. Math. Inform. 61, 1-14, 2025.

doi DEA

Folyóirat-mutatók:

Q4 Computer Science (miscellaneous)

Q4 Mathematics (miscellaneous)

10.

Leutbecher, M., Baran, S.: Ensemble size dependence of the logarithmic score for forecasts issued as multivariate normal distributions.
Q. J. R. Meteorol. Soc. 151 (766), 1-16, (cikkazonosító: 4898), 2025.

doi DEA WoS Scopus

Folyóirat-mutatók:

Q1 Atmospheric Science

11.

Baran, S., Marín, J. C., Cuevas, O., Díaz, M., Szabó, M., Nicolis, O., Nagy-Lakatos, M.: Machine learning-based probabilistic forecasting of solar irradiance in Chile.
Adv. Stat. Clim. Meteorol. Oceanogr. 11 (1), 89-105, 2025.

doi DEA Scopus

Folyóirat-mutatók:

Q1 Applied Mathematics

Q2 Atmospheric Science

Q1 Oceanography

Q2 Statistics and Probability

12.

Nagy, B. Á., Nagy, B. Á., Nagy, Á., Gáll, J., Sterbenz, T.: Offensive efficiency and traditional positional roles in Hungarian basketball: an empirical analysis.
Front. Sports Act. Living. 7, 01-12, (cikkazonosító: 1658662), 2025.

doi DEA

Folyóirat-mutatók:

D1 Anthropology

Q2 Orthopedics and Sports Medicine

Q1 Physical Therapy, Sports Therapy and Rehabilitation

Q2 Physiology

Q2 Public Health, Environmental and Occupational Health

Q2 Tourism, Leisure and Hospitality Management

13.

Rácz, A.: Optimization model for reducing inconsistency of pairwise comparison matrices with minimal change.
OPSEARCH. 62, 2272-2288, 2025.

doi DEA WoS Scopus

Folyóirat-mutatók:

Q3 Computer Science Applications

Q3 Information Systems

Q2 Management Information Systems

Q3 Management Science and Operations Research

14.

Nagy, B. Á., Nagy, B. Á., Nagy, Á., Gáll, J., Sterbenz, T.: Rethinking the Strongest Link: VAL, Ratings, and Team Success in Hungarian Basketball.
Front. Sports Act. Living. 7, 1-12, (cikkazonosító: 1658676), 2025.

doi DEA

Folyóirat-mutatók:

D1 Anthropology

Q2 Orthopedics and Sports Medicine

Q1 Physical Therapy, Sports Therapy and Rehabilitation

Q2 Physiology

Q2 Public Health, Environmental and Occupational Health

Q2 Tourism, Leisure and Hospitality Management

15.

Fazekas, I., Barta, A., Fórián, L., Porvázsnyik, B.: A continuous-time network evolution model describing N-interactions.
MATH. 9 (12), 35721-35742, 2024.

doi DEA WoS Scopus

Folyóirat-mutatók:

Q2 Mathematics (miscellaneous)

16.

Lakatos, R., Bogacsovics, G., Harangi, B., Lakatos, I., Tiba, A., Tóth, J., Szabó, M., Hajdu, A.: A Machine Learning-Based Pipeline for the Extraction of Insights from Customer Reviews.
Big Data Cogn. Comput. 8 (3), 1-24, 2024.

doi DEA WoS Scopus

Folyóirat-mutatók:

Q2 Artificial Intelligence

Q1 Computer Science Applications

Q1 Information Systems

Q1 Management Information Systems

17.

Baran, Á., Baran, S.: A two-step machine learning approach to statistical post-processing of weather forecasts for power generation.
Q. J. R. Meteorol. Soc. 150 (759), 1029-1047, 2024.

doi DEA WoS Scopus

Folyóirat-mutatók:

Q1 Atmospheric Science

18.

Baran, S., Nagy-Lakatos, M.: Clustering-based spatial interpolation of parametric post-processing models.
Weather Forecast. 39 (11), 1591-1604, 2024.

doi DEA WoS Scopus

Folyóirat-mutatók:

Q1 Atmospheric Science

19.

Antal, G., Szabó, S., Szarvas, P., Pusztahelyi, T., Gáll, J., Holb, I.: Cost-Benefit Analysis of Apple Scab Sanitation Practices for ULO-Stored Apple Fruit in Integrated and Organic Production Systems.
International Journal of Fruit Science. 24 (1), 1-17, 2024.

doi DEA

Folyóirat-mutatók:

Q2 Agronomy and Crop Science

Q2 Ecology

Q1 Horticulture

Q2 Plant Science

20.

Nagy-Lakatos, M., Baran, S.: Enhancing multivariate post-processed visibility predictions utilizing Copernicus Atmosphere Monitoring Service forecasts.
Meteorol. Appl. 31 (6), 1-19, (cikkazonosító: 70015), 2024.

doi DEA WoS Scopus

Folyóirat-mutatók:

Q2 Atmospheric Science

21.

Fazekas, I., Barta, A., Noszály, C., Porvázsnyik, B.: A continuous-time network evolution model describing 3-interactions.
Commun. Stat.-Theory Methods. 52 (11), 4001-4020, 2023.

doi DEA WoS Scopus

Folyóirat-mutatók:

Q3 Statistics and Probability

22.

Nagy-Lakatos, M., Lerch, S., Hemri, S., Baran, S.: Comparison of multivariate post-processing methods using global ECMWF ensemble forecasts.
Q. J. R. Meteorol. Soc. 149 (752), 856-877, 2023.

doi DEA WoS Scopus

Folyóirat-mutatók:

D1 Atmospheric Science

23.

Harangi, B., Baran, Á., Beregi-Kovács, M., Hajdu, A.: Composing Diverse Ensembles of Convolutional Neural Networks by Penalization.
Mathematics. 11 (23), 1-19, (cikkazonosító: 4730), 2023.

doi DEA Scopus

Folyóirat-mutatók:

Q2 Computer Science (miscellaneous)

Q2 Engineering (miscellaneous)

Q2 Mathematics (miscellaneous)

24.

Fazekas, I., Fórián, L., Barta, A.: Deep Learning from Noisy Labels with Some Adjustments of a Recent Method.
Infocommun. J. 15 (Special), 9-12, 2023.

doi DEA WoS Scopus

Folyóirat-mutatók:

Q3 Computer Science (miscellaneous)

Q3 Electrical and Electronic Engineering

25.

Szabó, M., Gascón, E., Baran, S.: Parametric Postprocessing of Dual-Resolution Precipitation Forecasts.
Weather Forecast. 38 (8), 1313-1322, 2023.

doi DEA WoS Scopus

Folyóirat-mutatók:

Q1 Atmospheric Science

Alkalmazott Matematikai és Valószínűségszámítási Tanszék

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